Triple
T10005168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CK One |
E198222
|
entity |
| Predicate | bottleDesignStyle |
P64696
|
FINISHED |
| Object | minimalist |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: minimalist | Statement: [CK One, bottleDesignStyle, minimalist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bottleDesignStyle Context triple: [CK One, bottleDesignStyle, minimalist]
-
A.
bottleFeature
chosen
Indicates that a bottle possesses or is characterized by a particular feature or attribute.
-
B.
hasBottleColor
Indicates that an entity is associated with a bottle characterized by a specific color.
-
C.
beerStyle
Indicates that one entity is the style or type classification of a beer associated with another entity.
-
D.
boltDesign
Indicates a design relationship where one entity specifies or defines the bolt configuration, features, or parameters used in another entity.
-
E.
wineStyle
Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca830fcca48190bbbd9b20c233835f |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd157d9c8190b863e4264f9a48b1 |
completed | April 2, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69cd1da2cf9081908a6c0eb5247d0bc2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:51 p.m.